As the rate of acquisition of biological data increases exponentially, the management, interrogation and manipulation of this data becomes a complex process that requires novel software solutions. Additionally, advancements in computational algorithms and massively parallel computing technology has enabled the application of chemical and physical modelling of increasingly complex biomolecular systems. The management of biological data, and the simulation and modelling of biological processes, form the foundations of the emerging field of Computational Biology, lying at the intersection between the biological and IT fields. There is a requirement for methodology to facilitate the acquisition, storage and retrieval of data, the analysis of this data, the accurate modelling of biophysical phenomena, and computationally complex tasks such as the prediction of macromolecular structure. This course will introduce these concepts and demonstrate some of the computational techniques currently available.

Objectives/Learning Outcomes/Capability Development

The objectives of this course are as follows:

Introduce the aims and uses of computational biology.

Describe the sources of data, in particular from the characterisation of genomes and proteomes.

Describe how biological information is stored and accurately retrieved.

Introduce computational algorithms that can be used for querying and manipulating biological data.

Students attend a formal program of lectures and computer workshops. There will also be independent learning.

Students are recommended to attend and participate in all scheduled teaching sessions and complete formal items of assessment to achieve satisfactory completion of the course. Formal teaching sessions are available only at the times specified and cannot be repeated. Students are expected to spend an appropriate amount of time out of classes reviewing theoretical and practical material in textbooks, journals and on the Internet, preparing self directed leaning exercises and writing reports.

Oral and written student evaluation of the course will be formally solicited and considered annually by the Program Team in course and program review.

Overview of Learning Resources

There is no textbook formally prescribed for this course. Most of the literature and documentation will be accessible via the internet or made available during classes. For a general introduction, the following texts are recommended: